NBAStates

Libraries

library(rvest)

## Loading required package: xml2

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(plotly)

## Loading required package: ggplot2

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(readr)

## 
## Attaching package: 'readr'

## The following object is masked from 'package:rvest':
## 
##     guess_encoding

讀取資料

states = read_csv("Seasons_Stats.csv")

## Parsed with column specification:
## cols(
##   .default = col_integer(),
##   Player = col_character(),
##   Pos = col_character(),
##   Tm = col_character(),
##   PER = col_double(),
##   TSp = col_double(),
##   FTr = col_double(),
##   OWS = col_double(),
##   DWS = col_double(),
##   WS = col_double(),
##   `WS/48` = col_double(),
##   `FG%` = col_double(),
##   TwoPp = col_double(),
##   `eFG%` = col_double(),
##   `FT%` = col_double()
## )

## See spec(...) for full column specifications.

TS%

tsp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(TSp, na.rm=TRUE))

plot_ly(tsp_by_year, x= tsp_by_year$Year ,y= tsp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))

## Warning: Ignoring 1 observations

2分球命中率變化

TwoPp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(TwoPp, na.rm=TRUE))

plot_ly(TwoPp_by_year, x= TwoPp_by_year$Year ,y= TwoPp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))

## Warning: Ignoring 1 observations

3分球命中率變化

ThreePp_by_year = states %>% group_by(Year) %>% summarise(mean=mean(ThreePp, na.rm=TRUE))

plot_ly(ThreePp_by_year, x= TwoPp_by_year$Year ,y= ThreePp_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))

## Warning: Ignoring 31 observations

罰球出手數變化

FTA_by_year = states %>% group_by(Year) %>% summarise(mean=mean(FTA, na.rm=TRUE))

plot_ly(FTA_by_year, x= FTA_by_year$Year ,y= FTA_by_year$mean, type = 'scatter',mode="markers",text = ~paste('Year: ', Year))

## Warning: Ignoring 1 observations